def custom_noise_configuration(remote_backend=_REMOTE_BACKEND_NAME):
    logger.info('Produce custom noise configuration')

    logger.info('Loading IBM account...')
    before = datetime.now()
    provider = IBMQ.load_account()
    delta = datetime.now() - before
    logger.info('IBM account loaded ({} s)'.format(delta.total_seconds()))

    device = provider.get_backend(remote_backend)
    coupling_map = device.configuration().coupling_map

    # QuantumError objects
    error_reset = pauli_error([('X', _P_RESET), ('I', 1 - _P_RESET)])
    error_meas = pauli_error([('X', _P_MEAS), ('I', 1 - _P_MEAS)])
    error_gate1 = pauli_error([('X', _P_GATE1), ('I', 1 - _P_GATE1)])
    error_gate2 = error_gate1.tensor(error_gate1)

    # Add errors to noise model
    noise_bit_flip = NoiseModel()
    noise_bit_flip.add_all_qubit_quantum_error(error_reset, "reset")
    noise_bit_flip.add_all_qubit_quantum_error(error_meas, "measure")
    noise_bit_flip.add_all_qubit_quantum_error(error_gate1, ["u1", "u2", "u3"])
    noise_bit_flip.add_all_qubit_quantum_error(error_gate2, ["cx"])

    return (noise_bit_flip, coupling_map)
Example #2
0
    def calculateEnergy(self, transpiledCircuit):

        if self.useNoiseModel == True:

            p_reset = 0.003
            p_meas = 0.01
            p_gate1 = 0.05

            # QuantumError objects
            error_reset = pauli_error([('X', p_reset), ('I', 1 - p_reset)])
            error_meas = pauli_error([('X', p_meas), ('I', 1 - p_meas)])
            error_gate1 = pauli_error([('X', p_gate1), ('I', 1 - p_gate1)])
            error_gate2 = error_gate1.tensor(error_gate1)

            noise_bit_flip = NoiseModel()
            noise_bit_flip.add_all_qubit_quantum_error(error_reset, "reset")
            noise_bit_flip.add_all_qubit_quantum_error(error_meas, "measure")
            noise_bit_flip.add_all_qubit_quantum_error(error_gate1, ["u1", "u2", "u3"])
            noise_bit_flip.add_all_qubit_quantum_error(error_gate2, ["cx"])

            simulator = QasmSimulator()

            job = execute(transpiledCircuit, backend=simulator, basis_gates=noise_bit_flip.basis_gates, noise_model=noise_bit_flip)
            results = job.result()
            counts = results.get_counts()

            _paulis, sgift = get_pauliList(self.ising, self.qubits)
            _basis = [(pauli[1], [i]) for i, pauli in enumerate(_paulis)]

            num_shots = sum(list(results.get_counts().values()))
            results = parallel_map(WeightedPauliOperator._routine_compute_mean_and_var,
                                   [([_paulis[idx] for idx in indices],
                                     results.get_counts())
                                    for basis, indices in _basis],
                                   num_processes=aqua_globals.num_processes)
            return results[0][0]

        else:
            _paulis, sgift = get_pauliList(self.ising, self.qubits)
            _basis = [(pauli[1], [i]) for i, pauli in enumerate(_paulis)]

            job = execute(transpiledCircuit, backend=self.backend)
            results = job.result()
            counts = results.get_counts()

            num_shots = sum(list(results.get_counts().values()))
            results = parallel_map(WeightedPauliOperator._routine_compute_mean_and_var,
                                   [([_paulis[idx] for idx in indices],
                                     results.get_counts())
                                    for basis, indices in _basis],
                                   num_processes=aqua_globals.num_processes)

            return results[0][0]
def test_process_characterisation_complete_noise_model() -> None:
    my_noise_model = NoiseModel()

    readout_error_0 = 0.2
    readout_error_1 = 0.3
    my_noise_model.add_readout_error(
        [
            [1 - readout_error_0, readout_error_0],
            [readout_error_0, 1 - readout_error_0],
        ],
        [0],
    )
    my_noise_model.add_readout_error(
        [
            [1 - readout_error_1, readout_error_1],
            [readout_error_1, 1 - readout_error_1],
        ],
        [1],
    )

    my_noise_model.add_quantum_error(depolarizing_error(0.6, 2), ["cx"],
                                     [0, 1])
    my_noise_model.add_quantum_error(depolarizing_error(0.5, 1), ["u3"], [0])
    my_noise_model.add_quantum_error(pauli_error([("X", 0.35), ("Z", 0.65)]),
                                     ["u2"], [0])
    my_noise_model.add_quantum_error(pauli_error([("X", 0.35), ("Y", 0.65)]),
                                     ["u1"], [0])

    back = AerBackend(my_noise_model)
    char = cast(Dict[str, Any], back.characterisation)

    dev = Device(
        char.get("NodeErrors", {}),
        char.get("EdgeErrors", {}),
        char.get("Architecture", Architecture([])),
    )

    assert char["GenericTwoQubitQErrors"][(0, 1)][0][1][0] == 0.0375
    assert char["GenericTwoQubitQErrors"][(0, 1)][0][1][15] == 0.4375
    assert char["GenericOneQubitQErrors"][0][0][1][0] == 0.125
    assert char["GenericOneQubitQErrors"][0][0][1][3] == 0.625
    assert char["GenericOneQubitQErrors"][0][1][1][0] == 0.35
    assert char["GenericOneQubitQErrors"][0][1][1][1] == 0.65
    assert char["GenericOneQubitQErrors"][0][2][1][0] == 0.35
    assert char["GenericOneQubitQErrors"][0][2][1][1] == 0.65
    assert dev.get_error(OpType.U3, dev.nodes[0]) == 0.375
    assert dev.get_error(OpType.CX, (dev.nodes[0], dev.nodes[1])) == 0.5625
    assert dev.get_error(OpType.CX, (dev.nodes[1], dev.nodes[0])) == 0.80859375
    assert char["ReadoutErrors"][0] == [[0.8, 0.2], [0.2, 0.8]]
    assert char["ReadoutErrors"][1] == [[0.7, 0.3], [0.3, 0.7]]
Example #4
0
def get_noise(noisy):
    """Returns a noise model when input is not False or None.
    A string will be interpreted as the name of a backend, and the noise model of this will be extracted.
    A float will be interpreted as an error probability for a depolarizing+measurement error model.
    Anything else (such as True) will give the depolarizing+measurement error model with default error probabilities."""
    if noisy:
        
        if type(noisy) is str: # get noise information from a real device (via the IBM Q Experience)
            device = get_backend(noisy)
            noise_model = noise.device.basic_device_noise_model( device.properties() )
        else: # make a simple noise model for a given noise strength
            if type(noisy) is float:
                p_meas = noisy
                p_gate1 = noisy
            else: # default values
                p_meas = 0.08
                p_gate1 = 0.04

            error_meas = pauli_error([('X',p_meas), ('I', 1 - p_meas)]) # bit flip error with prob p_meas
            error_gate1 = depolarizing_error(p_gate1, 1) # replaces qubit state with nonsense with prob p_gate1
            error_gate2 = error_gate1.kron(error_gate1) # as above, but independently on two qubits

            noise_model = NoiseModel()
            noise_model.add_all_qubit_quantum_error(error_meas, "measure") # add bit flip noise to measurement
            noise_model.add_all_qubit_quantum_error(error_gate1, ["u1", "u2", "u3"]) # add depolarising to single qubit gates
            noise_model.add_all_qubit_quantum_error(error_gate2, ["cx"]) # add two qubit depolarising to two qubit gates
            
    else:
        noise_model = None
    return noise_model
Example #5
0
    def test_backend_method_clifford_circuits_and_pauli_noise(self):
        """Test statevector method is used for Clifford circuit"""
        # Noise Model
        error = pauli_error([['XX', 0.5], ['II', 0.5]], standard_gates=True)
        noise_model = NoiseModel()
        noise_model.add_all_qubit_quantum_error(error, ['cz', 'cx'])

        # Test circuits
        shots = 100
        circuits = ref_2q_clifford.cz_gate_circuits_deterministic(
            final_measure=True)
        qobj = compile(circuits, self.SIMULATOR, shots=shots)

        def get_result():
            return self.SIMULATOR.run(
                qobj,
                backend_options=self.BACKEND_OPTS,
                noise_model=noise_model).result()

        # Check simulation method
        method = self.BACKEND_OPTS.get('method')
        result = self.SIMULATOR.run(
            qobj, backend_options=self.BACKEND_OPTS).result()
        self.is_completed(result)
        if method == 'statevector':
            self.compare_result_metadata(result, circuits, 'method',
                                         'statevector')
        else:
            self.compare_result_metadata(result, circuits, 'method',
                                         'stabilizer')
def get_noise_model(p_err):

    error_gate1 = pauli_error([("X", p_err / 2), ("Z", p_err / 2), ("I", 1 - p_err)])

    noise_model = NoiseModel()
    noise_model.add_all_qubit_quantum_error(error_gate1, "id")
    return noise_model
Example #7
0
    def test_backend_method_nonclifford_circuit_and_unitary_noise(self):
        """Test statevector method is used for Clifford circuit"""
        # Noise Model
        error = pauli_error([['XX', 0.5], ['II', 0.5]], standard_gates=False)
        noise_model = NoiseModel()
        noise_model.add_all_qubit_quantum_error(error, ['cz', 'cx'])

        # Test circuits
        shots = 100
        circuits = ref_non_clifford.ccx_gate_circuits_deterministic(
            final_measure=True)
        qobj = assemble(circuits, self.SIMULATOR, shots=shots)

        result = self.SIMULATOR.run(qobj,
                                    backend_options=self.BACKEND_OPTS,
                                    noise_model=noise_model).result()
        success = getattr(result, 'success', False)
        # Check simulation method
        method = self.BACKEND_OPTS.get('method', 'automatic')
        if method == 'stabilizer':
            self.assertFalse(success)
        else:
            self.assertTrue(success)
            if method == 'automatic':
                target_method = 'density_matrix'
            else:
                target_method = method
            self.compare_result_metadata(result, circuits, 'method',
                                         target_method)
Example #8
0
def get_noise(p_meas, p_gate):
    error_meas = pauli_error([('X', p_meas), ('I', 1 - p_meas)])
    error_gate1 = depolarizing_error(p_gate, 1)
    error_gate2 = error_gate1.tensor(error_gate1)

    noise_model = NoiseModel()
    noise_model.add_all_qubit_quantum_error(error_meas, "measure")
    noise_model.add_all_qubit_quantum_error(error_gate1, ["x"])
    noise_model.add_all_qubit_quantum_error(error_gate2, ["cx"])

    return noise_model
Example #9
0
def get_noise(p_meas, p_gate):
    """Define a noise model."""
    error_meas = pauli_error([("X", p_meas), ("I", 1 - p_meas)])
    error_gate1 = depolarizing_error(p_gate, 1)
    error_gate2 = error_gate1.tensor(error_gate1)

    noise_model = NoiseModel()
    noise_model.add_all_qubit_quantum_error(error_meas, "measure")
    noise_model.add_all_qubit_quantum_error(error_gate1, ["u1", "u2", "u3"])
    noise_model.add_all_qubit_quantum_error(error_gate2, ["cx"])

    return noise_model
Example #10
0
def get_noise(p_meas,p_gate):

    error_meas = pauli_error([('X',p_meas), ('I', 1 - p_meas)])
    error_gate1 = depolarizing_error(p_gate, 1)
    error_gate2 = error_gate1.tensor(error_gate1)

    noise_model = NoiseModel()
    noise_model.add_all_qubit_quantum_error(error_meas, "measure") # measurement error is applied to measurements
    noise_model.add_all_qubit_quantum_error(error_gate1, ["x"]) # single qubit gate error is applied to x gates
    noise_model.add_all_qubit_quantum_error(error_gate2, ["cx"]) # two qubit gate error is applied to cx gates
        
    return noise_model 
def test_process_characterisation_incomplete_noise_model() -> None:

    my_noise_model = NoiseModel()

    my_noise_model.add_quantum_error(depolarizing_error(0.6, 2), ["cx"],
                                     [0, 1])
    my_noise_model.add_quantum_error(depolarizing_error(0.5, 1), ["u3"], [1])
    my_noise_model.add_quantum_error(depolarizing_error(0.1, 1), ["u3"], [3])
    my_noise_model.add_quantum_error(pauli_error([("X", 0.35), ("Z", 0.65)]),
                                     ["u2"], [0])
    my_noise_model.add_quantum_error(pauli_error([("X", 0.35), ("Y", 0.65)]),
                                     ["u1"], [2])

    back = AerBackend(my_noise_model)
    char = cast(Dict[str, Any], back.characterisation)

    c = Circuit(4).CX(0, 1).H(2).CX(2, 1).H(3).CX(0, 3).H(1).X(0).measure_all()
    back.compile_circuit(c)
    assert back.valid_circuit(c)

    dev = Device(
        char.get("NodeErrors", {}),
        char.get("EdgeErrors", {}),
        char.get("Architecture", Architecture([])),
    )
    nodes = dev.nodes
    assert set(dev.architecture.coupling) == set([
        (nodes[0], nodes[1]),
        (nodes[0], nodes[2]),
        (nodes[0], nodes[3]),
        (nodes[1], nodes[2]),
        (nodes[1], nodes[3]),
        (nodes[2], nodes[0]),
        (nodes[2], nodes[1]),
        (nodes[2], nodes[3]),
        (nodes[3], nodes[0]),
        (nodes[3], nodes[1]),
        (nodes[3], nodes[2]),
    ])
Example #12
0
def get_noise_model(p_err):

    error_gate1 = pauli_error([("X", p_err / 2), ("Z", p_err / 2),
                               ("I", 1 - p_err)])
    error_gate2 = error_gate1.tensor(error_gate1)

    noise_model = NoiseModel()
    noise_model.add_all_qubit_quantum_error(
        error_gate1, "measure")  # measurement error is applied to measurements
    noise_model.add_all_qubit_quantum_error(
        error_gate1,
        ["u1", "u2", "u3"])  # single qubit gate error is applied to x gates
    noise_model.add_all_qubit_quantum_error(
        error_gate2, ["cx"])  # two qubit gate error is applied to cx gates

    return noise_model
Example #13
0
    def test_auto_method_clifford_circuits_and_unitary_noise(self):
        """Test statevector method is used for Clifford circuit"""
        # Noise Model
        error = pauli_error([['XX', 0.5], ['II', 0.5]], standard_gates=False)
        noise_model = NoiseModel()
        noise_model.add_all_qubit_quantum_error(error, ['cz', 'cx'])
        backend = self.backend(noise_model=noise_model)

        # Test circuits
        shots = 100
        circuits = ref_2q_clifford.cz_gate_circuits_deterministic(
            final_measure=True)
        result = backend.run(circuits, shots=shots).result()
        success = getattr(result, 'success', False)
        self.compare_result_metadata(result, circuits, 'method',
                                     "density_matrix")
Example #14
0
def get_noise(p):
    error_meas = pauli_error([('X',p), ('I', 1 - p)])
    noise_model = NoiseModel()
    noise_model.add_all_qubit_quantum_error(error_meas, "measure") # measurement error is applied to measurements        
    return noise_model
#
# `QuantumError` instances can be combined by using composition, tensor product, and tensor expansion (reversed order tensor product) to produce new `QuantumErrors` as:
#
#  * Composition: $\cal{E}(\rho)=\cal{E_2}(\cal{E_1}(\rho))$ as `error = error1.compose(error2)`
#  * Tensor product: $\cal{E}(\rho) =(\cal{E_1}\otimes\cal{E_2})(\rho)$ as `error error1.tensor(error2)`
#  * Expand product: $\cal{E}(\rho) =(\cal{E_2}\otimes\cal{E_1})(\rho)$ as `error error1.expand(error2)`

# ### Example
#
# For example to construct a 5% single-qubit Bit-flip error:

# In[2]:

# Construct a 1-qubit bit-flip and phase-flip errors
p_error = 0.05
bit_flip = pauli_error([('X', p_error), ('I', 1 - p_error)])
phase_flip = pauli_error([('Z', p_error), ('I', 1 - p_error)])
print(bit_flip)
print(phase_flip)

# In[3]:

# Compose two bit-flip and phase-flip errors
bitphase_flip = bit_flip.compose(phase_flip)
print(bitphase_flip)

# In[4]:

# Tensor product two bit-flip and phase-flip errors with
# bit-flip on qubit-0, phase-flip on qubit-1
error2 = phase_flip.tensor(bit_flip)